| 2025 | COLT | Optimization, Isoperimetric Inequalities, and Sampling via Lyapunov Potentials. | August Y. Chen, Karthik Sridharan |
| 2025 | ICML | System-Aware Unlearning Algorithms: Use Lesser, Forget Faster. | Linda Lu, Ayush Sekhari, Karthik Sridharan |
| 2025 | ICML | Online Learning with Unknown Constraints. | Karthik Sridharan, Seung Won Wilson Yoo |
| 2022 | ICML | Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation. | Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan |
| 2020 | COLT | Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations. | Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster, Ayush Sekhari, Karthik Sridharan |
| 2019 | ALT | Two-Player Games for Efficient Non-Convex Constrained Optimization. | Andrew Cotter, Heinrich Jiang, Karthik Sridharan |
| 2019 | COLT | The Complexity of Making the Gradient Small in Stochastic Convex Optimization. | Dylan J. Foster, Ayush Sekhari, Ohad Shamir, Nathan Srebro, Karthik Sridharan, Blake E. Woodworth |
| 2019 | ICML | Distributed Learning with Sublinear Communication. | Jayadev Acharya, Chris De Sa, Dylan J. Foster, Karthik Sridharan |
| 2019 | ICML | Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints. | Andrew Cotter, Maya R. Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Lutong Wang, Blake E. Woodworth, Seungil You |
| 2018 | AISTATS | Inference in Sparse Graphs with Pairwise Measurements and Side Information. | Dylan J. Foster, Karthik Sridharan, Daniel Reichman |
| 2018 | COLT | Logistic Regression: The Importance of Being Improper. | Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan |
| 2018 | COLT | Online Learning: Sufficient Statistics and the Burkholder Method. | Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan |
| 2018 | COLT | Small-loss bounds for online learning with partial information. | Thodoris Lykouris, Karthik Sridharan, va Tardos |
| 2017 | AISTATS | Efficient Online Multiclass Prediction on Graphs via Surrogate Losses. | Alexander Rakhlin, Karthik Sridharan |
| 2017 | COLT | ZigZag: A New Approach to Adaptive Online Learning. | Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan |
| 2017 | COLT | On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities. | Alexander Rakhlin, Karthik Sridharan |
| 2016 | AISTATS | Private Causal Inference. | Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger |
| 2016 | ICML | BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits. | Alexander Rakhlin, Karthik Sridharan |
| 2015 | AISTATS | Online Optimization : Competing with Dynamic Comparators. | Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan |
| 2015 | COLT | Learning with Square Loss: Localization through Offset Rademacher Complexity. | Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan |
| 2015 | COLT | Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints. | Alexander Rakhlin, Karthik Sridharan |
| 2014 | COLT | Online Non-Parametric Regression. | Alexander Rakhlin, Karthik Sridharan |
| 2013 | AISTATS | Localization and Adaptation in Online Learning. | Alexander Rakhlin, Ohad Shamir, Karthik Sridharan |
| 2013 | COLT | Competing With Strategies. | Wei Han, Alexander Rakhlin, Karthik Sridharan |
| 2013 | COLT | Online Learning with Predictable Sequences. | Alexander Rakhlin, Karthik Sridharan |
| 2013 | ITW | On Semi-Probabilistic universal prediction. | Alexander Rakhlin, Karthik Sridharan |
| 2012 | ICML | Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss. | Shai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan |
| 2012 | ICML | Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization. | Alexander Rakhlin, Ohad Shamir, Karthik Sridharan |
| 2011 | IJCAI | Learning Linear and Kernel Predictors with the 0-1 Loss Function. | Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan |
| 2010 | COLT | Robust Selective Sampling from Single and Multiple Teachers. | Ofer Dekel, Claudio Gentile, Karthik Sridharan |
| 2010 | COLT | Learning Kernel-Based Halfspaces with the Zero-One Loss. | Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan |
| 2010 | COLT | Convex Games in Banach Spaces. | Karthik Sridharan, Ambuj Tewari |
| 2009 | COLT | The Complexity of Improperly Learning Large Margin Halfspaces. | Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan |
| 2009 | COLT | Stochastic Convex Optimization. | Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan |
| 2009 | COLT | Learnability and Stability in the General Learning Setting. | Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan |
| 2009 | ICML | Multi-view clustering via canonical correlation analysis. | Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu, Karthik Sridharan |
| 2008 | COLT | An Information Theoretic Framework for Multi-view Learning. | Karthik Sridharan, Sham M. Kakade |
| 2006 | ICPR | Identifying Handwritten Text in Mixed Documents. | Faisal Farooq, Karthik Sridharan, Venu Govindaraju |
| 2006 | ICPR | Competitive Mixtures of Simple Neurons. | Karthik Sridharan, Matthew J. Beal, Venu Govindaraju |
| 2005 | IDEAL | A Dynamic Migration Model for Self-adaptive Genetic Algorithms. | K. G. Srinivasa, Karthik Sridharan, P. Deepa Shenoy, K. R. Venugopal, Lalit M. Patnaik |